Biology of Sex Differences最新文献

Background: Social determinants of health (SDOH) and clinical severity factors are known to shape substance use disorder (SUD) treatment outcomes, yet limited research has explored how these influences differ by sex. Understanding these differences is important to improving treatment equity and outcomes in publicly funded treatment systems.

Methods: This study analyzed data from the 2018-2022 Treatment Episode Data Set-Discharges (TEDS-D), a national dataset of adults discharged from publicly funded SUD treatment programs. Sex-stratified binary logistic regressions were used to examine predictors of two outcomes: treatment non-completion and substance use at discharge. Predictors included SDOH (i.e., employment, education level, housing status, criminal justice involvement, prior treatment history, marital status, health insurance coverage and treatment duration) and indicators of SUD severity (e.g., age at first use, polysubstance use, and co-occurring psychiatric disorders).

Results: Both SDOH and clinical severity indicators were significantly associated with poorer treatment outcomes, with distinct patterns by sex. Women showed more consistent risk for poor treatment outcomes across predictors, including unemployment, psychiatric comorbidities, and polysubstance use, while lack of prior treatment history was the strongest predictor of substance use at discharge and dropout for men. Other predictors, such as housing instability, criminal justice involvement, and later-onset substance use, were also associated with increased risk of non-abstinence and dropout, with notable sex differences. Health insurance coverage was associated with better outcomes for both sexes, with the protective effect more consistent in women.

Conclusions: These findings emphasize the need for sex-informed treatment approaches that address both social determinants of health and clinical complexity. Tailoring care to the unique risks and contexts of men and women may improve retention and reduce substance use at discharge, particularly in publicly funded systems. Highlights We examined social determinants of health (SDOH), and substance use disorder (SUD) severity-related predictors of substance use and treatment completion in a national sample of approximately 7 million adults. Women demonstrated more consistent vulnerability across predictors, including unemployment, co-occurring psychiatric disorders, and polysubstance use. For men, lack of prior treatment for SUD was the most consistent predictor for substance use at discharge and treatment dropout. Housing instability, access to healthcare, and financial barriers showed sex-specific effects, with women generally experiencing great risk of unsuccessful treatment. Findings highlight the importance of improving SUD care to address sex-specific risks and structural barriers, especially in publicly funded systems. Plain English Summa

Clinical risk calculators consider sex as a binary variable. However, sex is a complex trait with anatomic, physiologic, and metabolic attributes that are not easily summarized in this manner [1]. We propose a continuous representation of sex, the ECG Sex Index (ESI), derived via artificial intelligence analyses of electrocardiograms (ECG-AI).We used an ECG repository at Wake Forest Baptist Health (Winston-Salem, NC) to develop a convolutional neural network-based ECG-AI model to detect sex from standard 12-lead ECGs. We utilized a rank-ordered transformation of the outcomes of ECG-AI to create the ESI. We also created a sex discordance index (SDI) from the ESI and assessed its utility in 1-year risk prediction for all-cause mortality, heart failure, and kidney failure.The Wake Forest cohort included 3,573,844 ECGs and electronic health record data from 754,761 patients; 75% were White, 17% were Black, and 51% were female, with a mean age (SD) of 61 (17) years. The PhysioNet external validation cohort included 45,152 ECGs from 10,646 patients from two hospitals in China. The PhysioNet cohort was 100% Asian, 43.6% female, and had a mean age (SD) of 59 (20) years. ECG-AI provided a holdout area under the curve of 0.95 and an external validation area under the curve of 0.92. Lower ESI scores in males and higher ESI scores in females were associated with a greater risk for clinical outcomes. The ESI and SDI demonstrated comparable accuracy to binary sex in logistic regression analyses and outperformed binary sex in predicting clinical outcomes, highlighting their value as predictors in risk calculators for all-cause mortality, heart failure, and kidney failure.

Background: Frailty refers to a state of increased vulnerability to mortality and other adverse outcomes as a consequence of age-related physiological decline. Sex differences in frailty have been reported; women are usually more frail than men. Physical frailty in men and women is the result of both sociobehavioral and biological factors, making the deciphering of the biology of sex differences in frailty challenging. Investigators have measured frailty in aging animals, including mice and dogs. We posited that companion dogs provide a useful opportunity to study sex differences in the biology of frailty, circumventing many of the sociobehavioral determinants of frailty that complicate human studies.

Methods: Male-female differences in the relationship between lifetime gonad hormone exposure and late-life robustness were studied in the Exceptional Aging in Rottweilers Study (EARS), a lifetime cohort study of companion dogs with a broad range of lifetime gonad exposure. Late-life frailty was assessed by scoring dogs (135 females, 87 males) for deficit accumulation using a 34-item clinical frailty index previously developed and validated in dogs. The study outcome, late-life robustness, was defined as the lowest tertile of frailty index in the study population. Logistic regression models were constructed to assess differences in the likelihood of late-life robustness in dogs stratified into low, middle, and high lifetime gonad exposure groups. Male-female differences were probed after controlling for age at frailty scoring, gonad exposure, and other covariates.

Results: In both male and female dogs, there was a strong association between longer lifetime gonad exposure and increased likelihood of late-life robustness. Compared to dogs in the lowest gonad exposure group, dogs with highest gonad exposure had a statistically significant 3-fold (females) to 10-fold (males) higher likelihood of late-life robustness. Notably, after controlling for gonad exposure and age at frailty scoring, no male-female difference in late-life robustness was found.

Conclusions: The research extends current interest in the biology of sex differences in frailty and provides rationale for further inquiry into the role that the hypothalamic-pituitary-gonadal axis plays in supporting late-life robustness. Studies with companion dogs represent a unique investigative opportunity to enhance our understanding of biological factors that impact sex differences and to spur the development of sex-specific anti-frailty interventions.

Background: Our previous study on silver pomfret (Pampus argenteus) demonstrated that all gonads initially develop into ovaries by 60 days post-hatch (dph). Between 80 and 120 dph, some oocytes undergo apoptosis, resulting in the development of testes and a transient hermaphroditic stage. This observation indicates a complex molecular mechanism underlying sex differentiation in this species.

Methods: Gonadal samples were collected at 90 dph, 120 dph, and 150 dph, with sex identification performed by HE staining and transcriptome sequencing. Morphological traits, including body length and weight, were measured to evaluate sexual size dimorphism. Candidate genes related to with sex differentiation were identified through differential gene expression analysis and feature selection methods, followed by gene set enrichment analysis to identify potential molecular pathways. Heatmaps were generated to visualize gene expression patterns across developmental stages and samples. Sex hormones concentrations were measured using commercial assay kits to assess their role in gonadal differentiation. RT-qPCR validated the sequencing results, while immunofluorescence (IF) examined the expression of related genes in testes and ovaries.

Results: Histological and transcriptomic analyses identified the period between 90 and 120 dph as critical for sex differentiation in silver pomfret. At 90 dph, apoptotic signals trigger the apoptosis of early-stage oocytes. During this period, both testis-preferential and ovary-preferential genes exhibit high expression, leading to spermatogonia differentiation and the emergence of a juvenile hermaphroditic stage. The study established that androgens 11-KT and estrogen E2 regulate sex differentiation through modulation of related gene expression, with 11-KT serving a crucial role. This process involved significant enrichment of the steroid hormone biosynthesis pathway and the metabolism of xenobiotics by cytochrome P450 in the testes. Ovarian development is characterized by fatty acid metabolism and PPAR signaling pathway activation, along with energy metabolism pathways including the citrate cycle (TCA cycle) and cell degradation processes, such as lysosome activity and ubiquitin-mediated proteolysis, suggesting that ovarian development encompasses lipid accumulation and follicular selection.

Conclusions: This investigation illuminates the molecular processes underlying this distinctive pattern of gonadal differentiation, providing novel insights into sex differentiation in fish exhibiting a juvenile hermaphroditic stage.

Background: There is no safe amount or time of alcohol consumption during pregnancy; however, many women drink while pregnant placing themselves and their fetuses at risk for alcohol-related health complications. Social Determinants of Health (SDoH) impact alcohol use during pregnancy. Understanding the impact of SDoH across pregnancy will elucidate important information to reduce rates of prenatal alcohol exposure.

Methods: Cross-sectional data from the National Survey of Drug Use and Health from 2009 to 2019 was used to explore the impact of SDoH on alcohol use across pregnancy. The study assesses past month alcohol use and past month binge drinking, as well as various SDoH. The sample included 8,638 pregnant women.

Results: Over 9% of pregnant women reported alcohol use within the past 30 days and 5.25% reported drinking on three or more days within the past month. 3.65% reported past month binge drinking. Past month alcohol use and past month binge drinking decreased in the second and third trimesters; however, a subset of women continued alcohol use, including binge drinking. Specific SDoH emerged as increasing the likelihood of alcohol use within the past month, including not being married (ORs = 1.54 to 1.94), criminal justice involvement (arrested and booked; OR = 1.88), and past year psychiatric distress (OR = 1.86). Conversely, other determinants were associated with a lower likelihood of alcohol use, including identifying as Asian or Hispanic (ORs = 0.41 and 0.64) and unemployment (OR = 0.52) and other employment (OR = 0.66). Older age was associated with a lower likelihood of binge drinking within the past month (ORs = 0.32). Unique SDoH emerged when examining alcohol use by trimester.

Conclusion: Specific SDoH (i.e., not married, criminal justice involvement, past year psychiatric distress) are related to increased alcohol use during pregnancy, while other determinants (i.e., identifying as Asian or Hispanic, not requiring full time/part-time employment) are associated with a decreased risk for past month alcohol use. Older individuals (35-49 years old) and those with a high school education had a decreased likelihood of binge drinking. Accordingly, healthcare providers should screen all pregnant women for alcohol use throughout pregnancy, especially among populations or groups identified as being vulnerable to continue alcohol use during pregnancy.

Background: Obstructive sleep apnea (OSA) is associated with increased risks of glucolipid metabolic disruption, endocrine disturbances and psychological distress. There is scarce research regarding the influence of sex on these associations. The current study aimed to evaluate the effects of sex on metabolic, endocrine and psychological changes in patients with OSA.

Methods: One hundred sixty-four young adult women and one hundred sixty-two age-matched men with OSA completed polysomnography assessments, questionnaires (including the Epworth Sleepiness Scale [ESS], Self-Reported Anxiety Scale [SAS], Self-Rating Depression Scale [SDS], and 12-Item Short-Form Health Survey [SF-12]) and biochemical analyses for glucolipid metabolism and endocrine function, including the pituitary-adrenal (PA), pituitary thyroid (PT), and pituitary-gonadal (PG) axes.

Results: Homeostasis model assessment of insulin resistance (HOMA-IR), thyroid hormone and midnight PA axis activity levels were greater in female patients with severe OSA compared to those with mild-to-moderate OSA, and these metabolic and endocrine changes were associated with nocturnal hypoxia only in female patients. Additionally, midnight cortisol was associated with HOMA-IR (independent of anthropometry and sleep disturbance parameters) in females (β = 0.545, P = 0.012, adjusted R² = 0.217). ESS was higher for male patients with severe OSA compared to females with the same level of OSA (P = 0.003), and ESS was associated with nocturnal hypoxia in males (β = - 0.494, P = 0.001, adjusted R² = 0.224). SAS was higher for female patients with severe OSA compared to males with the same level of disease (P = 0.001).

Conclusions: The metabolic, endocrine and psychological consequences of OSA may differ across sexes. The associations of nocturnal hypoxia with glucose metabolic disturbance and the activation of the PA and PT axes were observed in females, whereas the association of nocturnal hypoxia with ESS was limited to males. This could indicate a distinct metabolic, endocrine and psychological phenotype for female patients with OSA, who may require different disease management strategies compared to males.

Background: Structural covariance within the brain is thought to reflect inter-regional sharing of developmental influences. This hypothesis has proved difficult to test but can be informatively probed by the study of sex differences. Here, we use neuroimaging in humans and mice to study sex-differences in anatomical covariance- asking (1) are there sex differences in structural covariance and (2) do regions that share the same developmental influences, as exhibited by shared sex differences in volume, also show shared sex differences in volume covariance. This study design illuminates both the biology of sex-differences and theoretical models for anatomical covariance- benefitting from tests of inter-species convergence.

Methods: Brain volume correlations for males and females across 255 regions in mice (n = 423) and 378 regions in humans (n = 436) were calculated using volumetric measures obtained from structural MRI. Mean correlations for each sex were compared within species to determine whether covariance sex differences exist. Specific covariances with strong sex differences in each species were identified via permutation tests for statistical significance. Brain maps of regional average structural covariance sex-bias were generated for mice and humans. Regional average structural covariance sex-bias and volumetric sex-bias were correlated to identify whether these features align in their direction of sex-bias.

Results: We find that volumetric structural covariance is stronger in adult females than males for both wild-type mice and healthy human subjects: 98% of comparisons with statistically significant covariance sex differences in mice are female-biased, while 76% of such comparisons are female-biased in humans (q < 0.05). Regional covariance and volumetric sex-biases have weak inverse relationships to each other in both species: volumetrically male-biased regions contain more female-biased covariations, while volumetrically female-biased regions have more male-biased covariations (mice: r = -0.185, p = 0.002; humans: r = -0.189, p = 0.001).

Conclusions: Our results identify a tendency for females to show stronger neuroanatomical covariance across species. These structural covariance sex differences are also partially related to regional sex differences in volume for both species, suggesting that stronger structural covariance in females could be an evolutionarily conserved feature - partially shaped by the same developmental influences that mediate volumetric sex-biases.

Background: Many women experience suboptimal cardiovascular health (CVH) during midlife. Greenspace exposure has been inversely associated with cardiovascular disease because it may reduce harmful environmental exposures and promote healthy behaviors. Most prior studies used satellite-based rather than ground-level exposures and did not examine overall CVH.

Methods: We performed a longitudinal analysis of women in the Project Viva cohort based in Eastern Massachusetts. We applied deep learning algorithms to Google Street View images to derive metrics of visible trees, grass, and other greenspace within 500 m of participant's residential addresses in 2012-2016 (mean age 46 years). About five years later (mean age 51 years), participants completed questionnaires and research measurements including blood collection. We calculated CVH scores using Life's Essential 8 (LE8) construct (0-100 points, higher = better), which includes four behavioral (diet, physical activity, sleep, and avoidance of smoking) and four biomedical measures (body mass index, blood pressure, blood lipids, and blood glucose). We used linear regression models adjusted for age and both individual- and neighborhood-level socioeconomic status.

Results: Among 767 participants, 68% were non-Hispanic White, and 74% were college graduates. Mean (SD) CVH score was 72 (13) points. When including three greenspace components in the same model, higher % trees (per SD) was associated with higher overall CVH score (β = 2.4; 95% CI: 1.3, 3.5), as well as higher behavioral (β = 2.8; 95% CI: 1.4, 4.3) and biomedical (β = 2.8; 95% CI: 1.0, 4.7) sub-scores. Additionally, % other greenspace (per SD) was associated with better biomedical CVH scores (β = 2.2; 95% CI: 0.4, 3.9), whereas associations for % grass were non-significant. Higher % trees (per SD) was associated with higher scores for most individual CVH components, including diet (β = 2.1 points; 95% CI: 0.7, 3.4), physical activity (β = 4.0; 95% CI: 1.2, 6.9), sleep (β = 2.6; 95% CI: 0.9, 4.4), BMI (β = 5.8; 95% CI: 2.8, 8.8), and blood glucose (β = 2.2; 95% CI: 0.3, 4.2).

Conclusions: Greater street-view greenspace exposure, especially visible trees in streetscapes, was associated with better CVH among midlife women. Increasing trees in neighborhoods may be a valuable public health strategy to improve multiple metrics of cardiovascular health.